Genome Biology (Apr 2023)

TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches

  • Mourdas Mohamed,
  • François Sabot,
  • Marion Varoqui,
  • Bruno Mugat,
  • Katell Audouin,
  • Alain Pélisson,
  • Anna-Sophie Fiston-Lavier,
  • Séverine Chambeyron

DOI
https://doi.org/10.1186/s13059-023-02911-2
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 20

Abstract

Read online

Abstract Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/DrosophilaGenomeEvolution/TrEMOLO .

Keywords